
What Students Say
Likes
- I liked the campus infrastructure. The buildings, labs and classrooms feel modern and well maintained. The environment is clean and organised, which makes it easier to focus.
- I liked that there are regular fests, events and club activities. If I want exposure, networking or stage confidence, there are opportunities.
- CSE gets decent placement attention. Companies do come regularly, and the placement cell conducts training sessions, mock interviews and aptitude practice.
Dislikes
- Attendance pressure feels unnecessary sometimes. Too much focus on rules and compliance instead of actual learning
- Some classes are heavily PPT-based. A few professors just rush to finish the syllabus without going deep into concepts.
- Practical exposure could be stronger. For an AI-ML program, more real-world projects and industry-level work would help.
Course Curriculum Overview
I’d rate the curriculum about 7/10. I chose AI-ML because it includes subjects like programming, data structures, machine learning and AI, which are relevant today. The structure gives a strong foundation and helps for higher studies. It prepares me with basics, but it’s not enough alone for industry-level skills. I still need self-learning, coding practice and real projects outside class. Improvements needed: more hands-on AI projects, less slide-based teaching, and stronger industry exposure. Each semester has internal tests, a mid-sem and an end-sem exam. Exams are moderate in difficulty and mostly test syllabus understanding
Internships Opportunities
Internships usually come up in 3rd/5th semester (summer breaks) so students can get real-world experience before final placements. Many internships are for academic credit and some come with stipends depending on the company and role. Through the placement cell and industry partnerships, students get opportunities with big tech and consulting firms — either directly or through networks of recruiters and partners: Amazon – tech/data related internships Microsoft – based on Azure, cloud or dev tools Google – project/tech internships Deloitte – tech/analytics/consulting roles IBM – development/test automation tasks Infosys – software development or agile project internships
Placement Experience
Students become eligible for campus placements from the 5th semester (3rd year) onwards, and internships often start from the same time. The placement season runs in the final year with companies visiting from October to March. Big companies like Amazon, Adobe, Deloitte, TCS, Wipro, Infosys, IBM, Microsoft and Oracle come for drives, and many smaller firms also hire. Highest packages reported recently are up to ?1.11 crore (mainly from Amazon), and average packages across engineering are around ?8–10 lakh per annum. Placement percentage is pretty high (80–95%) if a student actively participates and prepares well. Many students get placed on Day 1 itself during drives. Most offers are in software development, IT, data roles, consulting and product teams. Top companies also give super dream offers (10 LPA+) to a good chunk of students. In short: campus placements are strong for CSE/AI-ML if I prepare well. The support from the placement cell helps with training and interview prep, but final results still depend largely on my skills.
Fees and Financial Aid
I pay around ?1.5 lakh per semester for CSE AI-ML at Chitkara, so that’s roughly ?3–3.2 lakh per year. Over 4 years, tuition comes to about ?14–15 lakh. This covers tuition, labs, exams and academic charges. Hostel, mess and transport are separate. If I stay in hostel for all 4 years, total spending can reach around ?18–20 lakh. Fees usually increase slightly for new batches, but once I’m admitted, my structure mostly stays the same with minor changes in admin or exam charges. There’s no major fee difference for General, SC, ST or OBC since it’s a private university. If someone pays less, it’s usually because of a scholarship. Scholarships are mainly merit-based, need-based or sports-based, and they can reduce tuition by around 10–50% depending on eligibility. Government scholarships are separate and applied through official portals.
Campus Life
Campus life is active and fun. The university hosts big cultural festivals like Chit Utsav (national youth fest) and huge freshers’ parties like Sunburn Campus, usually around Jan–Feb and Sep–Oct every year. There are lots of student clubs — photography (Club Tasveer), dance groups (Bhangra Regiment, Lethal Giddha), art, music (Club Dhwani), theatre, literary and more — and they make life social and creative. The library is strong — big reading halls, group discussion rooms and access to tons of e-books and journals, plus comfy spaces to study. Classrooms and labs are well-equipped with projectors, computers and modern facilities that actually help learning. Sports is alive here — cricket, basketball, football, volleyball, tennis, badminton, table tennis, chess, gym and more, with regular competitions. There are also cultural celebrations like Teej and Lohri that bring everyone together, making the campus feel lively and connected. Social life is easy — tons of activities, student events and group projects keep things interesting. Alumni events and guest fest appearances also add to the vibe. Overall, it’s balanced between fun, culture and academics.
Admission
got into thapar coe feild was expensive tho; its easy to get into as long as u have money u can get in more or less ;also passing the basicI had to meet two main things: 12th pass with PCM (Physics, Chemistry, Maths) and at least 60% overall or 60% in PCM subjects. Appear in the JEE Main exam — the university expects a valid JEE Main score for engineering admissions 12th exam.
Faculty
Faculty-to-student ratio is average — one professor handles around 50–60 students. Most teachers are approachable if I go to them personally, but they won’t chase me. The relationship depends on how proactive I am. Some professors are genuinely good — they explain concepts clearly and relate them to real-world applications instead of just reading slides. Those are the best ones. A few others rely heavily on PPTs and rush the syllabus, which makes classes feel mechanical. The exam system includes internal tests, assignments, a mid-sem exam, and an end-sem exam. Marks are usually split between internal assessment and final exam. Exams are moderate in difficulty. If I study regularly, they’re manageable. Most students pass unless they ignore attendance or don’t prepare. The curriculum is relevant to AI-ML basics, but it’s not very deep. Real skill depends on how much extra effort I put in outside class.
Night Life
Nightlife around my campus is honestly calm, not crazy. Chitkara’s main campus is slightly outside the city area, so it’s not like metro nightlife. Inside campus, things slow down after evening. The library usually closes by evening (around 6–8 PM depending on schedule). Academic blocks shut after classes. Cafeterias run till evening; late-night options inside campus are limited. The gym operates during fixed hours, mostly morning and evening slots. Hostel life is where most of the “nightlife” happens. There are in-timings for hostels (stricter for girls). After entry time, movement outside isn’t allowed without permission. Students usually unwind by hanging out in hostel rooms, watching movies, gaming, group studying, or late-night conversation














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